BACKGROUND/AIMS: High sodium intake is associated with adverse cardiovascular and renal outcomes in people with chronic kidney disease (CKD), and simple methods to facilitate assessment of sodium intake are required. The objective of this study was to develop a new formula to estimate 24-hour urinary sodium (24hUNa) excretion from urinary Na concentration measured on an early morning urine specimen (EM UNa). METHODS: Seventy participants from a prospective cohort of patients with CKD stage 3 in primary care, the Renal Risk in Derby (RRID) study, agreed to collect an additional EM UNa on the day after completing a 24-hour urine collection. A formula to estimate 24hUNa from EM UNa and body weight was developed using the coefficients from a multivariable linear regression equation. The accuracy of the formula was tested by calculating the P30 (proportion of estimates within 30% of measured sodium exection), and the ability of the estimated 24hUNa to discriminate between measured sodium intake above or below 100 mmol/day was assessed by receiver operating characteristic (ROC) curve. A Bland-Altman plot was used to estimate the bias and limits of agreement between estimated and measured 24hUNa. Seventy-four additional paired 24hUNa and EM UNa from 50 CKD stage 3 patients in the RRID study were used to validate the formula. RESULTS: The mean difference between measured and estimated 24hUNa was 2.08 mmol/day. Measured and estimated 24hUNa were significantly correlated (r = 0.55; p < 0.001) but accuracy of estimated 24hUNa was low (P30 = 60%). Analysis of the ROC curve with a cut-off point >100 mmol/day yielded an area under the curve of 0.668, sensitivity of 0.85 and specificity of 0.52. CONCLUSIONS: We have developed a simple formula to identify people with a high sodium intake from EM UNa, suitable for use in large-cohort or population studies.